Book description
This textbook introduces chemistry and chemical engineering students to molecular descriptions of thermodynamics, chemical systems, and biomolecules.- Equips students with the ability to apply the method to their own systems, as today's research is microscopic and molecular and articles are written in that language
- Provides ample illustrations and tables to describe rather difficult concepts
- Makes use of plots (charts) to help students understand the mathematics necessary for the contents
- Includes practice problems and answers
Table of contents
- Cover
- Preface
- Acknowledgments
- About the Companion Website
- Symbols and Constants
- 1 Introduction
- 2 Review of Probability Theory
-
3 Energy and Interactions
- 3.1 Kinetic Energy and Potential Energy of Atoms and Ions
- 3.2 Kinetic Energy and Potential Energy of Diatomic Molecules
- 3.3 Kinetic Energy of Polyatomic Molecules
- 3.4 Interactions Between Molecules
- 3.5 Energy as an Extensive Property
- 3.6 Kinetic Energy of a Gas Molecule in Quantum Mechanics
- Problems
-
4 Statistical Mechanics
- 4.1 Basic Assumptions, Microcanonical Ensembles, and Canonical Ensembles
- 4.2 Probability Distribution in Canonical Ensembles and Partition Functions
- 4.3 Internal Energy
- 4.4 Identification of β
- 4.5 Equipartition Law
- 4.6 Other Thermodynamic Functions
- 4.7 Another View of Entropy
- 4.8 Fluctuations of Energy
- 4.9 Grand Canonical Ensembles
- 4.10 Cumulants of Energy
- Problems
- 5 Canonical Ensemble of Gas Molecules
- 6 Indistinguishable Particles
- 7 Imperfect Gas
- 8 Rubber Elasticity
- 9 Law of Mass Action
- 10 Adsorption
- 11 Ising Model
- 12 Helical Polymer
- 13 Helix–Coil Transition
- 14 Regular Solutions
- Appendix A: Mathematics
- References
- Index
- End User License Agreement
Product information
- Title: Statistical Thermodynamics
- Author(s):
- Release date: March 2019
- Publisher(s): Wiley
- ISBN: 9781118305119
You might also like
book
Quantum Machine Learning: An Applied Approach: The Theory and Application of Quantum Machine Learning in Science and Industry
Know how to adapt quantum computing and machine learning algorithms. This book takes you on a …
book
Clean Python: Elegant Coding in Python
Discover the right way to code in Python. This book provides the tips and techniques you …
book
Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow, 3rd Edition
Through a recent series of breakthroughs, deep learning has boosted the entire field of machine learning. …
book
Understanding Digital Signal Processing
Amazon.com’s Top-Selling DSP Book for Seven Straight Years—Now Fully Updated! is quite simply the best resource …